library(tidyverse)
library(janitor)
library(lubridate)
deprivation <- read_csv(here::here("raw_data/admissions_by_hb_and_deprivation.csv")) %>%
clean_names()
dep_date <- deprivation %>%
mutate(
year = str_extract(week_ending, "^\\d{4}"),
monthday = str_extract(week_ending, "\\d{4}$"),
month = str_extract(monthday, "^\\d{2}"),
day = str_extract(monthday, "\\d{2}$"),
date = ymd(str_c(year, month, day)), .after = 1
)
dep_date$simd_quintile <- as_factor(dep_date$simd_quintile)
library(plotly)
ggplotly(dep_date %>%
group_by(date, simd_quintile) %>%
summarise(avg_admissions = mean(number_admissions)) %>%
ggplot() +
aes(x = date, y = avg_admissions, colour = simd_quintile) +
geom_line())
`summarise()` has grouped output by 'date'. You can override using the `.groups` argument.
```r
input = list(
)
```
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